autonomic problem solving

Self-Healing in Mobile Networks


Mobile Network Self-Healing

Deep learning for log pattern recognitions

Utilizing deep learning models, we provide analysis of log data for recognition and classification of anomalous log patterns.

Machine learning for degradation detections in metric data

Models are trained for recognition of degradation in metrics, both for uni- and multi-variate time series data.

Event correlation

Each anomaly detected and represented as an island makes no use. We put them together in the unit of situational awareness which we call observation using Dataverse Event Correlation engine.

Healing actions

Based on detected anomalies and information gathered via situational awareness (correlation) engine, the specific healing action is constructed in relation to mulitple parameters. Action is either directly invoked by Dataverse ActionExec orhcestrating mechanism, or information is provided on the message bus for any other orchestrator to perform the needed action.


What do you get with Self-Healing solution

Continuous monitoring

Heterogeneous data in one place for easy correlations

Convenient and fast system for deep data insights

Faster fault detection

Act before customer complaints

Prevention of more serious issues


Observability pipelines with autonomic decisions

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